Beta-binomial distribution
In probability theory and statistics, the beta-binomial distribution is a family of discrete probability distributions on a finite support of non-negative integers arising when the probability of success in each of a fixed or known number of Bernoulli trials is either unknown or random. The beta-binomial distribution is the binomial distribution in which the probability of success at each of n trials is not fixed but randomly drawn from a beta distribution. It is frequently used in Bayesian statistics, empirical Bayes methods and classical statistics to capture overdispersion in binomial type distributed data.
Probability mass function | |||
Cumulative distribution function | |||
Notation | |||
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Parameters |
n ∈ N0 — number of trials (real) (real) | ||
Support | x ∈ { 0, …, n } | ||
PMF |
where is the beta function | ||
CDF |
where 3F2(a;b;x) is the generalized hypergeometric function | ||
Mean | |||
Variance | |||
Skewness | |||
Excess kurtosis | See text | ||
MGF | where is the hypergeometric function | ||
CF | |||
PGF |
The beta-binomial is a one-dimensional version of the Dirichlet-multinomial distribution as the binomial and beta distributions are univariate versions of the multinomial and Dirichlet distributions respectively. The special case where α and β are integers is also known as the negative hypergeometric distribution.